Last post I wrote I said I’d continue with a process for structuring and synthesising the information we gather from the initial contact we make with the person. This process is integral to clinical reasoning, and somewhat surprisingly, there’s not a great deal of research to give us guidance on the best way to do this – and it’s even more challenging for those of us working in an interprofessional team setting, where different professions, personalities and assumptions are part of it.
If we work backwards from the end point, we might get some clues about what to do. Our end point is to help this person do what matters in their life. All our efforts are pitched towards this end. Because people are unique, what matters to them in their context is likely to be unique, and because pain and disability are multifactorial, there will be many paths to help that person get to where they want to be. Algorithms are designed to make the task of clinical reasoning a lot simpler, but there are some enormous assumptions associated with using an algorithmic approach: that we know the important factors associated with change; that we can address those factors successfully; that each person has the same set of factors evident in their presentation… and frankly, I don’t think I’ve seen strong evidence of any of these when it comes to pain.
Clinical reasoning is about a series of cause and effect assumptions. We have limited certainty about much of pain and the relationships between factors we think influence pain and disability. We’ve also been holding on to some outdated and inaccurate assumptions about the way grouped data applies to the one person in front of us. Prof Steven Hayes points out that as early as the 1940’s (perhaps earlier) we knew that there was no such thing as “the average man” (or woman!). This emerged in human factors/ergonomic design, where using the average/median of all the anthropomorphic measures we have does not help us design a workstation or control panel that will work for all people. Instead, we have to design to suit the minimum and maximum clearances and reach, and add adjustability so that everyone can make their workstation work for them. The assumptions used in early application of anthropometrics were that everyone is essentially similar: it’s ergodic theory (https://en.wikipedia.org/wiki/Ergodic_theory). Ergodic theory holds two assumptions that don’t work well for people: all the events in ergodic theory must be stationary, and all elements in the mathematical model must obey they same rules.
When we work with people, we know their presentation is a series of responses that continue to move over time. Their presentation is dynamic, changing all the time but exhibiting similarities in terms of processes. And we also know that different factors influencing a person’s presentation don’t always follow the same patterns. There are things like legislation, unexpected events like trauma or earthquakes, biases and stigma – and these don’t affect everyone equally.
One solution is to acknowledge this and instead look to the particular, applying to this person at this time – idiographic, or as Hayes calls it “idionomic.” A network diagram, showing the dynamic hypothesised relationships between contributing factors can help us generate ways to influence change. And the diagram should “make sense”, or explain, what’s going on to all the team members including the person with pain.
I’ve used a cognitive behavioural formulation model for many years now (see here and here – and use the search bar for “case formulation” for a list of the posts I’ve made over the years). The assumptions in this approach are that directly influencing the thoughts a person has about their pain will have flow-on effects on pain, emotions, actions and physiological arousal. And to a certain extent this is true – plus, there are some things we cannot readily change, such as family responses or previous trauma. But the flexibility of a formulation approach is that we can include anything that’s relevant including strategies the person has used in response to those things that can’t be changed.
The biggest assumption that I make is that pain on its own isn’t the main problem. It’s how we respond to pain, what we think is going on, how we react to the things we do in response to pain (or things we don’t do but think we should), and how the people around us influence us, that help determine how much pain bothers us. There is plenty of research showing that people willingly do painful things if they do so for important reasons. Some everyday examples include ritual tattoos, endurance sports, boxing and martial arts, eating very spicy chilli. Of course, these aren’t examples of persistent pain – and yet, people with persistent pain started with acute pain. There are some highly influential factors that are present from the outset and these do have an impact on how we respond to pain, especially as time goes on.
The second assumption I make is that everyone is able to learn how to do things differently, and in doing these, we can develop a different relationship with pain and become less distressed and disabled by our experience. This doesn’t mean (a) that we should just give up and be resigned to a life of pain and not seek treatment to reduce pain; or (b) that we should just ignore pain and grit teeth and bear it. It also doesn’t mean that we will feel happy about pain, or that life goes on as normal. But it does mean that we can make some room for pain to be present, and move towards doing what matters rather than having pain become some invisible barrier to a life worth living.
Exactly what we include, and how the relationships between each factor play out is the topic for next weeks’ blog – stay in touch!